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Eco-efficiency is a vital tool for evaluating and advancing regional sustainable development. This study presents an urban eco-efficiency (UEE) framework that deserves widespread application. By using the Super Slacks-Based Measure model, the research calculates the UEE of 284 prefecture-level cities in China from 2005 to 2022. The study employs the Standard Deviational Ellipse to illustrate the spatiotemporal pattern of UEE in China and examines its effects using non-parametric kernel density estimation, the coefficient of variation, and both global and local Moran's I. The integration of UEE with urban development patterns, which is not immediately clear, is achieved through the entropy-based TOPSIS model. Additionally, the Malmquist index, the Two-way Fixed Effects (TWFE) model, and the Panel Vector Autoregression (PVAR) model reveal the dynamic changes and interactive driving mechanisms of UEE in China. The results indicate that: (1) UEE in China displays a consistent “core-periphery” pattern, exhibiting a notable hierarchical impact from regional, scale, and administrative perspectives. The complexity of UEE's spatiotemporal variations has increased due to the impact of COVID-19. (2) The UEE of Chinese cities shows a significant ‘club’ effect, with efficiency thresholds for high-high and low-low aggregations set at 0.8. (3) Only 25% of Chinese cities have achieved optimal UEE levels. Notably, cities in the west contribute most to national UEE growth, while midland cities contribute the least. The decreasing trend in UEE growth underscores the urgent need for a shift in China's urban development model. (4) UEE in China benefits from a resilient self-reinforcing mechanism, with urban development and economic growth significantly aiding UEE growth. Despite a non-significant negative impact from government intervention, the inhibitory effect of an intensive industrial structure on UEE turns into a promotional effect, especially following COVID-19.

Since 1978, China's rapid urbanization and industrialization have significantly increased carbon emissions. This study employs spatial autocorrelation, kernel density estimation, and spatiotemporal geographically weighted regression (GTWR) methods to analyze the spatiotemporal evolution characteristics of carbon emissions across 336 Chinese cities from 1978 to 2020. It also explores the dominant influencing factors for different cities at various stages of development. The findings reveal that carbon emissions in Chinese cities exhibit a stepwise growth pattern: “slow growth (1978–1995) - low-level stability (1996–2000) - rapid growth (2001–2012) - high-level stability (2013–2020).'' The gap between cities has widened rapidly, and spatially, the distribution follows a “core-periphery” pattern. The increase in carbon emissions in core cities has transformed the urban hierarchy from a “generally low-carbon” structure to a “pyramid” structure. Compared to 1995, the influence of population size on carbon emissions decreased in 2020 (0.54–0.38), while the impact of infrastructure development and technological advances increased (0.02–0.25, 0.09 to 0.19). Due to the varying stages of urban development across regions, the influencing factors of carbon emissions exhibit spatial heterogeneity. Specifically, population size has a stronger positive impact on carbon emissions in the Southeast, technological advances in East and North China, and industrial structure in the Yangtze River Basin region. Infrastructure construction and investment levels show a dampening effect on carbon emissions in the Yangtze River Basin. Finally, the study proposes policy recommendations focusing on implementing regional “gradient” carbon reduction and promoting regional collaborative carbon reduction driven by core cities.

Extreme heat events occur frequently in urban areas, seriously affecting human well-being and productivity. Therefore, this article aimed to quantify the impact of and regional differences in the urban heat island (UHI) effect within the broader context of achieving sustainable development goals. To this end, we combined footprint analysis with principal component analysis and multivariate linear regression analysis to quantify the spatiotemporal distribution of heat island intensity and footprint within the Beijing–Tianjin–Hebei urban agglomeration as well as the impact of regional differences. We found that the surface urban heat island intensity (SUHII) value was higher during the daytime than at night. In 2005, 2010, 2015, and 2018, the average daytime values of SUHII were 0.21°C, 0.03°C, 0.35°C, and 0.53°C higher than those at night, respectively. High daytime values of SUHII mainly occurred in larger cities (e.g., Beijing), and high nighttime values of SUHII mainly occurred at higher latitudes. In addition, we determined that the maximum values of the SUHIF were concentrated in densely populated areas such as Beijing, Tianjin, and Shijiazhuang. Furthermore, principal component analysis revealed that PM2.5 was negatively correlated with SUHII, whereas population density (PD) and enhanced vegetation index were positively correlated with SUHII. In contrast, PM2.5 and EVI were negatively correlated with SUHIF, whereas PD and SUHIF showed a negative correlation. This article elucidates the changes in and influencing mechanisms of the UHI intensity and footprint and provides an important reference for mitigating the UHI effect and rationally planning urban land use.

Understanding the response of land surface temperature (LST) to urbanization is important for coping with urban warming. However, few studies have discussed the impact of twin-city integration on LST. Here, we explored the relationship between the twin-city integration and LST over the Xi'an-Xianyang Metropolitan Area (XXMA) using the local contour tree algorithm during 2000–2020. Results indicate that: 1) The urban integration of XXMA is obvious, and the spatial scope of XXMA converges toward the Weihe River between the two cities. Besides, its structure tends to be more complex, which develops from 3 levels and 8 centers to 10 levels and 33 centers from 2000 to 2020. 2) The heat islands of XXMA tend to connect and reach the maximum area of 547.43 km2 in 2015, while the LST evolution in two cities is not synchronized. The LST contour tree of Xi'an increased to 6 levels and 26 centers in 2000–2015 and simplified to 5 levels and 17 centers in 2020, while it increased from 1 to 4 levels in Xianyang in 2000–2020. 3) Synergistic effects exist between urban expansion and LST evolution. The correlation coefficient and bivariate Moran's I between nighttime light (NTL) and LST are greater than 0.35, indicating NTL and LST are correlated and have pleasurable spatial consistency. The high–high agglomeration of NTL and LST increases by 132% in area over the 20-year period, showing a trend toward integration. The study results can provide a scientific basis for thermal environment management and urban climate improvement in XXMA.

Summary: Global warming has led to a surge in heat health risks (HHRs), the impacts of which are particularly pronounced in metropolitan areas of developing countries. In the current study, six metropolitan areas - Beijing, China; Cairo, Egypt; Jakarta, Indonesia; Mumbai, India; Rio de Janeiro, Brazil; and Tehran, Iran - were selected as the study area to further differentiate the built-up landscapes by utilizing the concept of local climate zones. Moreover, we assessed the similarities and differences in HHR associated with the landscape. Results revealed a 30.67% higher HHR in compact built-up landscapes than in the open built-up type. Urban green spaces played an effective but differentiated role in mitigating HHR. That is, low vegetation in urbanized areas and trees in suburban areas significantly mitigated HHR. Collectively, our findings emphasize the role of effective planning and management in addressing HHR and provide empirical support for implementing HHR mitigation and adaptation strategies.

In investigating the spatiotemporal patterns and spatial attributes of carbon storage across terrestrial ecosystems, there is a significant focus on improving regional carbon sequestration capabilities. Such endeavors are crucial for balancing land development with ecological preservation and promoting sustainable, low-carbon urban growth. This study employs the integrated InVEST-PLUS model to assess and predict changes in ecosystem carbon storage under various land use scenarios within the Chengdu urban cluster, a vital region in Central and Western China, by 2050. The results indicate the following. (1) A linkage between land use dynamics and ecosystem carbon storage changes: over two decades, a 7.5% decrease in arable land was observed alongside a 12.3% increase in urban areas, leading to an 8.2% net reduction in ecosystem carbon storage, equating to a loss of 1.6 million tons of carbon. (2) Carbon storage variations under four scenarios—natural development (NDS), urban development (UDS), farmland protection (FPS), and ecological protection (EPS)—highlight the impact of differing developmental and conservation policies on Chengdu’s carbon reserves. Projections until 2050 suggest a further 5% reduction in carbon storage under NDS without intervention, while EPS could potentially decrease carbon storage loss by 3%, emphasizing the importance of strategic land use planning and policy. This research provides a solid theoretical foundation for exploring the relationship between land use and carbon storage dynamics further. In summary, the findings highlight the necessity of incorporating ecological considerations into urban planning strategies. The InVEST-PLUS model not only sheds light on current challenges but also presents a method for forecasting and mitigating urbanization effects on ecosystem services, thus supporting sustainable development goals.

The urban development boundary (UDB) is a core issue in territorial spatial planning and remains a research focus in urban development. However, in the past, land use simulations of coastal cities have had some limitations. For example, new urban land outside the research boundary could not be effectively simulated, resulting in a large gap between the simulation results and reality. In this study, an artificial neural network (ANN) cellular automata (CA) model based on a new perspective, the Offshore Island Connection Line (collectively, OICL-ANN-CA), was developed to address this problem. We first proposed the delineation principles and methods of OICL and applied it to the Jinpu New Area of Dalian City, Liaoning Province, China. Based on the conversion probability and land use simulation results obtained by ANN and CA, this study validated the UDB simulations for 2000–2020 in the Jinpu New Area and predicted the UDB for 2020–2035 under three scenarios: historical inertia development, ecological security protection, and ecological and economic balance. The results indicate that, compared with the traditional perspective model (the ANN-CA model based on the sea–land boundary), the OICL-ANN-CA model exhibited better simulation accuracy (the figure of merit was approximately 35% higher) and effectively simulated new urban land outside the traditional boundary. This simulation of urban land expansion is more consistent with recent development in the study area. In addition, the predicted results of UDB in 2035 also demonstrate the benefits of this model for detecting reclaimed land. This study illustrates that the OICL-ANN-CA model is a more capable method for capturing changes in new coastal urban land and can produce realistic simulations. It provides a reference for delimiting the UDB and defining the research boundary for the Jinpu New Area and other fast-growing coastal cities in China.

Under the robust impetus of China’s rural revitalization strategy, agro-tourism integration and tourism-driven poverty reduction have profoundly impacted various aspects of China’s economy, society, and ecology. This has propelled coordinated urban–rural development and the sustainable development of the tourism industry. This study introduces an analytical framework encompassing tourism-driven poverty reduction, agro-tourism integration, and rural revitalization. Through PVAR and threshold models, it empirically examines the interactive effects, dynamic relationships, and threshold effects between agro-tourism integration, tourism-driven poverty reduction, and rural revitalization. The conclusions are as follows: Firstly, the indices of rural revitalization and the level of agro-tourism integration show an increasing trend across Chinese provinces, with varying trends in tourism-driven poverty reduction efficiency. Secondly, there is a significant dynamic relationship among these factors, with the explanatory power of tourism-driven poverty reduction and agro-tourism integration gradually strengthening. Agro-tourism integration is identified as the most effective means of driving rural revitalization, while tourism-driven poverty reduction has a relatively weaker direct impact. Thirdly, tourism-driven poverty reduction exhibits a positive impulse response to agro-tourism integration. The improvement in tourism-driven poverty reduction efficiency propels further development in agro-tourism integration, thereby fostering rural revitalization. The efficiency of tourism-driven poverty reduction presents a single threshold effect in the process of agro-tourism integration promoting rural revitalization. Fourthly, the development of China’s tourism industry has become an indispensable means of promoting rural revitalization and poverty reduction. However, rural revitalization is a comprehensive project influenced by various factors, requiring improvements and development across multiple aspects.

Rapid urbanization has tremendously changed the urban ecological spaces and function of regional habitats, threatening regional ecological security and landscape sustainability. Understanding the impact of urban expansion on habitat quality is significant to ecological security. However, research on habitat quality and ecological security patterns in arid desert regions is limited. Given the research gap, this study constructed and optimized the ecological security pattern of Jiziwan (which refers to areas similar to the shape of the Chinese character “几”) in the Yellow River Basin. To achieve the aim, high habitat quality areas obtained from the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model were used as “sources”, and ecological corridors were identified from the Minimal Cumulative Resistance (MCR) model. Simultaneously, this study integrated land use, natural, social, and economic factors to monitor and assess the impact of urban expansion on habitat quality in Jiziwan. The results showed that: (1) urban expansion and ecological land have become more fragmented in Jiziwan and the urban expansion has changed from the edge-expansion type to the outlying type; (2) from 2000 to 2020, the urban expansion rate increased from 25.95% to 97.58%, which was negatively correlated with the rate of change in good habitat quality; (3) we finally identified 45 important ecological corridors, 140 secondary ecological corridors, and 44 ecological nodes that form an ecological spatial pattern of “two barriers, three corridors, and seven zones”. Our analytical framework offers a valuable tool for constructing ecological security patterns in Jiziwan and selecting “sources” at the regional scale. It can be applied to other landscapes and geographical contexts for sustainable development in arid regions.

Understanding the thermal characteristics and contribution ranking of local climate zones (LCZs) is essential since they can help in maintaining environmental harmony. However, previous studies only considered independent effects and could not analyze the combined effects of LCZ on land surface temperature (LST). In this study, we propose a new method to establish an interaction model between LCZs. Five first-level grids with different scales from 270 to 990 m were established to calculate the area proportion of LCZ. The area proportion of LCZ was then applied in the stepwise regression model to quantitatively analyze its magnitude and direction of impact on the LST. The results suggest that the LCZ types of the study area with the highest and lowest average LST were LCZ2 (compact middle-rise building, 39.82°C) and LCZG (water body, 34.24°C), respectively. However, on most scales, the warming effect of LCZ2 was lower than that of LCZE (bare rock or paver), and the cooling effect of LCZG was lower than that of LCZD (low plants). The optimum results were obtained at a scale of 810 m. At this scale, the warming effect was in the order: LCZE (0.314) > LCZ2 (0.236) > LCZ3 (compact low-rise building, 0.135) > LCZ5 (open middle-rise, 0.084) > LCZ6 (open low-rise, 0.056); the cooling effect was in the order: LCZD (−0.272) > LCZA (dense trees, −0.104) > LCZG (−0.103). These findings can help to elucidate the unique warming and cooling effects of LCZ on the interaction condition and the construction of an urban human settlement.

China’s energy consumption and its growth trend determine the domestic energy production and supply pattern. The understanding of energy consumption and its changes will help to enhance urban resilience. Based on the improved input-output model and hypothesis extraction model, this paper aims at constructing the energy-industry connection model, analyzing the energy transfer implied in the economic activities of various industrial sectors, and examining the energy transfer effect between the supply-side (SS) and demand-side industry sectors of the Shaanxi Province. The results showed that, in 2017, the energy industrial sector was the most energy consumption industry in Shaanxi Province. The industrial energy sector belonged to the net energy output industrial sector, and the energy products were transferred to other industrial sectors. This paper can provide a scientific basis for the energy SS reform, adjusting the industrial layout of regions in the Yellow River Basin.

Exploring the factors that drive the change of ecosystem services (ES) is very important for maintaining ES function and zoning ecological management, especially in the Sichuan Basin area with high spatial heterogeneity such as natural and socio-economic characteristics. Taking the Sichuan Basin in China as an example, the PCA-MGWR model was constructed to explore the temporal and spatial patterns of ES in the Sichuan Basin from 2000 to 2015. The potential driving factors including anthropogenic factors, geomorphological factors, climate factors, and vegetation factors would be analyzed by principal component analysis (PCA). To illustrate the impact of spatial dependence in the data, the multi-scale geographically weighted regression (MGWR) technology was selected to explore the spatial differentiation of the impact of these four dimensions on ES to reflect the local differences of ecosystem service driving mechanisms in more detail. The results showed that 1) from the perspective of time series evolution, carbon storage (CS) and soil conservation (SC) in ES in the Sichuan Basin showed an upward trend, while water yield (WY) showed a downward trend; from the perspective of spatial patterns, except the main urban areas of Chengdu and Chongqing, the CS service level of other regions was high; The spatial distribution characteristics of SC services were “low in the middle and high in the periphery”; the high value area of WY service was located in Northeast Sichuan. 2) Among natural factors, elevation (DEM), slope (SLO), NDVI, annual average temperature (TEM), and annual average precipitation (PRE) had a higher contribution rate to ES, while among socio-economic factors, GDP density (GDP), night light (LIG), and population density (POP) had a higher contribution rate to ES, while other factors had a lower contribution rate. 3) Combined with the PCA-MGWR model, we analyzed the comprehensive response and spatial differentiation of driving factors to ES in the Sichuan Basin and explained in detail the influence of anthropogenic factors, geomorphological factors, climatic factors, and vegetation factors and their spatial heterogeneity in ES. It is expected that the spatial differences in the impact degree of different indicators can be considered when formulating the countermeasures of ES in the Sichuan Basin, to provide theoretical support for the implementation of regional ecological management and control.

The composition of human settlements is important to resolving urban issues, such as land shortage, and to rationally distributing human settlements and social resources. Based on the demand hierarchy theory, this paper comprehensively used the methods of location entropy, information entropy, and geographic detector to analyze the characteristics and driving mechanism of the specialization, composition, and compatibility of human settlements at all levels. (1) The composite characteristics of human settlements were influential; that is, clear concentration differences were found among various types of human settlements, with the specialization of primary human settlements having the highest concentration. The specialization of human settlements was characterized as center–periphery; that is, the centrality of basic and high-level human settlements was obvious and the discreteness of primary human settlements was obvious. (2) The spatial differences in the north–central–south compositions of human settlements were also influential. These spatial differences showed that the composite characteristics of the basic high-level and intermediate high-level human settlements were similar, and the composite features were weakly affected by the scale of the elements. (3) Furthermore, single human settlements were dominant, and the multi-level human settlements that were compatible with the comprehensive composite form were the primary form of expression. The interactions between the primary and other human settlements were relatively high. Finally, (4) the high-level human settlement elements and regional economic vitality were the dominant factors of the composite characteristic heterogeneity of human settlements. Residential self and social attributes have an impact on the diversity of their needs, and they interact with human settlements through human settlement elements. The results of the study are of great significance to the rational allocation of human settlements and the promotion of the composition of human settlements.

The urban environment is a complex system featuring interactions between nature and humans. Scant research on urban areas has analyzed and assessed urban heat islands (UHIs) from the perspectives of nature and humans. This article analyzes the spatio-temporal characteristics of UHIs in Hangzhou in China in the context of the relationship between nature and humans based on the standard deviational ellipse, Pearson correlation analysis, and principal component analysis (PCA). The results show the following: First, from 2000 to 2020, the coverage of UHIs in the main urban area of Hangzhou decreased, but areas with subhigh temperatures and high temperatures increased. Second, from 2000 to 2020, the main axis of the spatial development of UHIs persisted along the northwest–southeast direction. The spatial pattern of UHIs in Hangzhou was closely related to the direction of urban development. Third, the results of PCA show that socio-economic activities, surface coverage and topography were the major factors influencing UHIs in Hangzhou. Finally, natural factors have slowed the development of UHIs while human factors have aggravated their formation, where the former contributed more significantly to them than the latter. For each unit of change in nine factors that were considered, the surface temperature in the study area decreased by 0.166 units.

Resource-based urban agglomerations often encounter greater challenges in the sustainable development of human settlements. The aim of this study is to propose an approach to the coordinated development of competitiveness by analyzing the interaction of human settlements competitiveness (HSC) in resource-based urban agglomerations. Through the compound evaluation model of HSC and urban network analysis, this study finds: 1) the HSC measure increased from 35.12 in 1990 to 52.15 in 2015 and showed a downward trend from 2015 to 2019, with an average value of 47.82 in 2019; 2) The change trend of the relevance network density is the same as that of the HSC, while the difference network density reaches the lowest value of 0.441 when the HSC is the highest, indicating that the HSC of the urban agglomerations has improved to a certain extent but is more unsustainable, and 3) Communities in the relevance network are obviously bounded by the borders of provinces or urban agglomerations, while the communities in the difference network are differentiated into two types: high-competitiveness and low-competitiveness. Using the theory of “co-opetition” to analyze the sustainable development path of resource-based urban agglomerations, the study believes that a coordination mechanism and a guarantee mechanism for benefit distribution should be established between urban agglomerations to curb local protectionism, and promote regional dislocation development. The development gradient level also should be established within the urban agglomeration to narrow the gap between HSC of cities, and innovative development should be the core of promoting industrial transformation and upgrading.

Climate is a dominant factor affecting the potential geographical distribution of species. Understanding the impact of climate change on the potential geographic distribution of species, which is of great significance to the exploitation, utilization, and protection of resources, as well as ecologically sustainable development. Betula platyphylla Suk. is one of the most widely distributed temperate deciduous tree species in East Asia and has important economic and ecological value. Based on 231 species distribution data points of Betula platyphylla Suk. in China and 37 bioclimatic, soil, and topography variables (with correlation coefficients < 0.75), the potential geographical distribution pattern of Betula platyphylla Suk. under Representative Concentration Pathway (RCP) climate change scenarios at present and in the 2050s and 2070s was predicted using the MaxEnt model. We analyzed the main environmental variables affecting the distribution and change of suitable areas and compared the scope and change of suitable areas under different climate scenarios. This study found: (1) At present, the main suitable area for Betula platyphylla Suk. extends from northeastern to southwestern China, with the periphery area showing fragmented distribution. (2) Annual precipitation, precipitation of the warmest quarter, mean temperature of the warmest quarter, annual mean temperature, and precipitation of the driest month are the dominant environmental variables that affect the potential geographical distribution of Betula platyphylla Suk. (3) The suitable area for Betula platyphylla Suk. is expected to expand under global warming scenarios. In recent years, due to the impact of diseases and insect infestation, and environmental damage, the natural Betula platyphylla Suk. forest in China has gradually narrowed. This study accurately predicted the potential geographical distribution of Betula platyphylla Suk. under current and future climate change scenarios, which can provide the scientific basis for the cultivation, management, and sustainable utilization of Betula platyphylla Suk. resources.

Studying land comprehensive carrying capacity (LCCC) is the foundational and key requirement for determining land development planning and urban spatial development patterns of a region. However, the traditional evaluation method discounts the fuzziness and randomness of the evaluation index and its results. The cloud model combines randomness and fuzziness to reveal the correlation between randomness and fuzziness using numerical feature entropy and is used to represent the granularity of a qualitative concept. This study used the Liaoning Province as the study area, and developed a multi-dimensional evaluation index system for LCCC using a normal cloud model. Based on this, the relationship between the different elements of geological condition, resources and environment, economic scale and urban construction were studied using the coupling coordination degree model that reflected not only the system interactions but also the strengths of its degree of coordination. Our results were as follows: (1) numerical feature entropy were evaluated to determine the carrying capacity level of the land, and comprehensive land carrying capacity evaluations were conducted in terms of both quantitative results and the reliability of the results, promoting the scientific application of uncertainty theory in the field of comprehensive land evaluation as well as carrying capacity. (2) Liaoning Province’s prefecture-level cities had distinctly different LCCC, demonstrating “low in the west and high in the east” spatial distribution characteristics. Cities with established economies and relatively strong infrastructures had larger comprehensive land carrying capacities. Overall, there was considerable consistency across the region, though the “low in the west and high in the east” spatial distribution characteristics affected the degree of coordination.

In this paper, an integrated system based on low-concentrated photovoltaic/thermal (LCPV/T) technology and efficient vacuum membrane distillation (VMD) seawater desalination utilizing the energy of solar is established. Through a theoretical analysis and a series of experiments, this paper explores the temperature change of a single VMD process, and the variation trend of single-day membrane flux with solar irradiation and temperature parameters. In addition, the changes in solar irradiation, temperatures of the integrated system, membrane flux, and thermoelectric properties in different seasons are also analyzed. A mathematical model was established to calculate the relationship between membrane flux and temperature difference. The experimental results show that the membrane flux of VMD is 2.73 L/(m2·h); the simulated seawater can achieve a desalination rate of 99.9%. After economic analysis, the operating incomes of the system under sunny weather conditions in different seasons were all positive.

Chlorophyll-a(chl-a) has been used as an important indicator of water quality. Great efforts have been invested to develop remote-sensing-based chl-a retrieval models. However, due to the spatial difference in chl-a concentration, a single model usually cannot accurately predict the whole range of chl-a concentration. To test the performance of precedent chl-a models, we carried out an experiment along the upper and middle reaches of the Kaidu River and around some small ponds in the Bayanbulak Wetland. We measured water surface reflectance in the field and analyzed the chl-a concentration in the laboratory. Initially, we performed a sensitivity analysis of the spectrum band to chl-a concentration with the aim of identifying the most suitable bands for various chl-a models. We found that the water samples could be divided into two groups with a threshold of 4.50 mg/m3. Then, we tested the performance of 11 precedent chl-a retrieval models and 7 spectral index-based regression models from this study for all the sample datasets and the two separate datasets with relatively high and low chl-a concentrations. Through a complete comparison of the performance of these models, we selected the D3B model for water bodies with high chl-a concentration and OC2 model (ocean color 2) for low chl-a concentration waters, resulting in the hierarchical and piecewise retrieval algorithm OC2-D3B. The chl-a concentration of 4.50 mg/m3 corresponded to the D3B value of −0.051; therefore, we used −0.051 as the threshold value of the OC2-D3B model. The result of the OC2-D3B model showed a better performance than the other algorithms. Finally, we mapped the spatial distribution and seasonal pattern of chl-a concentration in Bayanbulak Wetland using Sentinel-2 images from 2016 to 2019. The results indicated that the chl-a concentration in the riparian ponds was generally in the range of 8–10 mg/m3, which was higher than that in rivers with a range of 2–4 mg/m3. The highest chl-a concentration usually appears in summer, followed by spring and autumn, and the lowest in winter. The correlation between meteorological data and chl-a concentration showed that temperature is the dominant factor for chl-a concentration changes. Our analytical framework could provide a better way to accurately map the spatial distribution of chl-a concentration in complex river systems.

Since economic globalization is unstable, it is difficult for the traditional open economic development model to meet the requirements of China’s development, and there is an urgent need for new ideas and models to be reoriented. Based on the analysis of the development mechanism of China’s open economy at this stage, we used the entropy method, Theil coefficient, Gini coefficient, and spatial Durbin model (SDM) to analyze the spatio-temporal pattern and influencing factors of the high-quality development level of the open economy in the Yangtze River Delta Area (YRDA). The results indicated that during the study period, the development level and development difference of open economy were on the rise, and the spatial difference in different regions was significant. The development of open economy was affected by many factors, and there was a spatial spillover effect. Based on the existing problems, at the stage of high-quality economic development, the YDRA should seize the opportunities brought by the new development pattern, improve government services, optimize innovation drive, and promote the development of open economy to a higher level. We believe that the results of this study can also provide relevant experience for the development of open economy in other regions of China.

Public health emergencies are characterized by significant uncertainty and robust transmission, both of which will be exacerbated by population mobility, threatening urban security. Enhancing regional resilience in view of these risks is critical to the preservation of human lives and the stability of socio-economic development. Network resilience (NR) is widely accepted as a strategy for reducing the risk of vulnerability and maintaining regional sustainability. However, past assessments of it have not sufficiently focused on its spatial effect and have overlooked both its internal evolution characteristics and external threats which may affect its function and effectiveness. Therefore, we used the Yangtze River Delta Region (YRDR) as a case study and conceptualized an integrated framework to evaluate the spatial pattern and mechanisms of NR under the superposition of the COVID-19 pandemiv and major holidays. The results indicated that the topology of a population mobility network has a significant effect on its resilience. Accordingly, the network topology indexes differed from period to period, which resulted in a decrease of 17.7% in NR. For network structure, the Shanghai-Nanjing and Shanghai-Hangzhou development axes were dependent, and the network was redundant. In the scenario where 20% of the cities were disrupted, the NR was the largest. Furthermore, the failure of dominant nodes and the emergence of vulnerable nodes were key factors that undermined the network’s resilience. For network processes, NR has spatial effects when it is evolute and there is mutual inhibition between neighboring cities. The main factors driving changes in resilience were found to be GDP, urbanization rate, labor, and transportation infrastructure. Therefore, we propose a trans-scale collaborative spatial governance system covering “region-metropolitan-city” which can evaluate the uncertain disturbances caused by the network cascade effect and provide insights into the sustainable development of cities and regions.

The process of urbanization is accelerating, and land surface temperature (LST) is increasing, seriously threatening human health. Therefore, it is crucial to explore the differences in LST of different land use/land cover (LULC) types. Using MOD11A2 and MCD12Q1 data, this study explored the seasonal differences in LST of each LULC type from the perspective of different climate zones. The results showed that the maximum and minimum LSTs during the day were higher than those at night. During the day, the LSTs of urban and built-up and barren lands were higher than those of forests, grasslands, and water bodies; at night, the LSTs of urban and built-up lands decreased but remained high, while barren lands showed a significant decrease to LSTs even lower than those of water bodies. In addition, the difference in daytime LST of the LU16 type (barren lands) in different climatic zones was the most obvious and was much higher than that of other LULC types in the middle temperate and south temperate zones, but much lower than those in the middle subtropical and north subtropical zones. This comparison of the LST differences of each LULC type under different climate backgrounds provides an important reference for rational urban planning.

The equity of transport accessibility is a prerequisite for sustainable development targets, especially in the ecologically fragile area of the Tibetan Plateau (also known as the Qinghai-Tibet Plateau). The relationship between transportation supply and social demand has become a key element of socioeconomic development and environmental protection in agricultural and pastoral areas. Based on data from transportation networks, permanent populations and the economy, this study uses a network analysis model, the coefficient of variation and the Gini coefficient to construct an index of social demand in townships and analyse the equity of transport accessibility on the Tibetan Plateau between 1980 and 2017; the principle of geographic distribution and the spatial relationship between transport accessibility and social demand at the township scale are also discussed. This study finds the following: the development of transportation has improved accessibility on the Tibetan Plateau, creating a highly accessible region with important cities as the nodes and major traffic arteries as the axes; both the coefficient of variation of transport accessibility and the Gini coefficient have increased slightly; and the equity of transport accessibility among townships on the Tibetan Plateau has exhibited a downward trend. Further, the social demand index is doubling every ten years, the spatial distribution has regional characteristics, and a decrease in permanent populations is the main reason for declining social demand index scores among townships. Townships with the lowest and highest social demand index scores for transportation development enjoy greater transportation benefits; there is a significant spatial relationship between social demand and location conditions (potential accessibility); the aggregation of social demand and accessibility types follows specific geographical distribution principles; and the Mangya-Gongshan Line delineates the distribution characteristics of township clusters with low social demand and low accessibility.

Metropolitan areas are important for engaging in fierce global competition. Cities in metropolitan areas in China are generally characterized by a core-periphery structure. The Yangtze River Delta metropolitan area (YRD) is a national strategic region in which Shanghai, as a central city, drives the economic growth of hinterland cities. Exploring the spatiotemporal characteristics and influencing factors between the central city and its hinterland cities in the YRD can provide a basis for promoting regional development. Based on the headquarters-branches and enterprise investment data from 1978 to 2019, this study analyzes the spatiotemporal characteristics and influencing factors of enterprise linkages between Shanghai and its hinterland cities in the YRD. Our results reveal the following: (1) the headquarters-branch linkages between Shanghai and its hinterland cities manifest polarization characteristics, with different polarized characteristics among the three provinces; (2) the enterprise investment linkages between Shanghai and its hinterland cities are getting closer, but the key cities for investment in each province are different; (3) economic strength is a core factor that affects whether Shanghai establishes enterprise branches in its hinterland cities; and (4) the enterprise investment linkages between Shanghai and its hinterland cities depend on whether a city has a comparative advantage.

The accurate identification of urban functional areas is of great significance for optimizing urban spatial structure, rationally allocating spatial elements, and promoting the sustainable development of the city. This paper proposes a method to precisely identify urban functional areas by coupling Open Street Map (OSM) and Point of Interest (POI) data. It takes the central urban area of Hangzhou as a case study to analyze the spatial distribution characteristics of the functional areas. The results show that: (1) The central urban areas of Hangzhou are divided into 21 functional areas (6 single functional areas, 14 mixed functional areas and 1 comprehensive functional area). (2) The single functional areas and the mixed functional areas show the geographical distribution characteristics of the looping stratification, which means "Core-periphery" differentiation is obvious, and the comprehensive functional area is relatively scattered. (3) The mixed degree of regional function with ecological function and production function is low while comprehensive functional areas are usually associated with higher potential and vitality. (4) The identification results are in great agreement with the actual situation of Hangzhou central urban area, and the method is feasible. Therefore, this paper can provide a reference for urban development planning and management.

With increased uncertainty and instability worldwide, how to enhance the urban economy resilience effectively has become one main issue for urban economic development. Based on the measurement of the economic resilience of 241 cities at the prefecture level and above in China using the sensitive index method, we scrutinize the impact of industrial specialization agglomeration and diversification agglomeration on urban economic resilience. Results indicate that, during the impact resistance period, industrial diversification agglomeration, especially related industrial diversification agglomeration, can enhance urban economic resilience, whereas industrial specialization agglomeration has no positive effect. In contrast, during the period of recovery and adjustment, industrial specialization agglomeration can improve urban economic resilience, and industrial diversification agglomeration, especially related industrial diversification agglomeration, has no positive effect. Further analysis indicates that, under the interaction of specialization and diversification agglomerations, the effect of industrial agglomeration on urban economic resilience depends on the type of dual industrial agglomeration, showing remarkable heterogeneity. This study may provide useful references for policy makers concerned with urban resilience.

With the development of globalization and informatization, the relationships among cities have become closer, and a “network” paradigm in urban studies is gaining attention. To examine China’s urban network evolution in a long time series, we used flow-based data to measure enterprise linkages from 1978 to 2019. We investigated the spatiotemporal evolution and complexity characteristics of urban networks in China and arrived at the following conclusions. (1) Intercity enterprise linkages in China have been continuously strengthened. The scale and density of urban networks have increased rapidly. Although the distribution of node cities’ importance and influence has been significantly unbalanced, the degree of which has lessened over time. (2) Network density has significantly improved since 1978, gradually forming a monocentric (Beijing) radial pattern. From the beginning of the twenty-first century, the status of core nodes (e.g., Shanghai) has gradually become prominent. Finally, four vertices stood out in 2019, forming a stable diamond structure. The spatial connection flows of enterprises constituted the core networks with Beijing as the center, skeleton networks with trunk lines formed by subnodes, and regional networks covering a wide range of peripheral areas. (3) China’s urban networks were typically small-scale and scale-free. However, the scale-free characteristics were weakened after 2010. The overall scale gap of intercity enterprise linkages gradually narrowed, and the structure of urban networks became optimized. Meanwhile, the urban networks were heterogeneous. There were more cities with headquarter-branches and active investment behaviors, which had strong influence and control over networks, playing their functions of “broker” and “transfer.”

Strategic emerging industries (SEIs) are an important industrial policy to promote innovation, develop advanced manufacturing, and upgrade the economy in China. The research explores the impact of SEIs on urban economic growth in mainland China, from agglomeration externalities and network externalities. The results show that SEIs have a significant impact on growth, and network externalities are generally more important than agglomeration externalities. Although the agglomeration of large-scale listed enterprises in the city promotes growth, too many large enterprises in the cluster, that is, the lack of small and medium-sized supporting enterprises, will harm urban growth. Meanwhile, a city with a higher degree of centrality has a larger GDP, but the strength has a negative impact.

From the perspective of the production–living–ecological space, this paper reclassifies the land-use categories in the central and southern Liaoning urban agglomeration in the years 1990, 2000, 2010 and 2018. It then quantitatively analyzes the spatiotemporal evolution characteristics of land-use transitions by adopting the land-use transfer matrix and other methods. This paper further uses the eco-environmental quality index and ecological contribution rate to explore the eco-environmental effects of the land-use transition. Finally, it identifies the influencing factors of the eco-environmental effect and the spatial differentiation law of the effect in the study area through the multi-scale geographically weighted regression (MGWR) model. The main conclusions reached are as follows: (1) During the study period, a slow increase was seen in the ecological land of the central and southern Liaoning urban agglomeration. A sharp decline occurred in the production land, and a rapid rise was found in the living land. (2) From 1990 to 2018, the eco-environmental quality index in the study region showed significant spatial differentiation, with the distribution characteristics being high in the east and low in the west. The areas have expanded and spread along the Shenyang-Dalian axis to form medium-low quality agglomerations. The encroachment of agricultural production land and urban and rural living land on forest ecological land is the main contributor to the deterioration of the eco-environmental quality during the study period. (3) Compared with the geographically weighted regression model and the ordinary least squares model, a remarkable advancement can be seen in the MGWR model, which is more suitable for research on the influencing factors of eco-environmental quality. In addition, different influencing factors have significant spatial differences in the degree and scale of impact.

Taking Dalian, a typical square city in China, as an example based on data from remote sensing images, questionnaires, spatial statistics, social economy, etc., 48 squares in the main districts were constructed from the perspective of human settlements in order to build five systems: nature, humanity, society, residence and support. The aim was to explore the spatio-temporal differentiation characteristics and their driving mechanism. The results show the following: (1) The index system was constructed based on the human settlements perspective, and PCA was used to comprehensively evaluate it. Four principal component factors were extracted, and their cumulative contribution rate is 78.701%. On this basis, city squares were divided into four types: comprehensive square, recreational square, commercial service square and traffic square. (2) Using Mapinfo to visualize the square space, and taking the People’s Square as the center, the squares from the Tsarist Russia and Japanese colonial rule time periods were mainly distributed within 5 km, mostly in the direction of NE-SEE. During the construction of New China, city squares were distributed in all directions of the city, mainly between NE-SE and NNW-SSW. (3) ArcGIS was used to create an analysis chart of square service scope. Compared with 1999, it was more concentrated in central cities in 2016, and the service scope was relatively small. However, a square with high popularity has a wider influence. (4) The formation and evolution of the spatial pattern of city squares are affected by many factors, such as nature, economy, society, politics, ecological environment and technology. In the planning and development of city squares, Dalian should pay full attention to human settlements perpectives and add luster to the development of livable cities.

Scholars have conducted a large number of empirical studies on agglomeration externalities and network externalities at the urban scale, but there are relatively few studies at the urban agglomeration scale. For the integrated development of the Yangtze River Delta (YRD), analyzing the impact of network externalities and agglomeration externalities on urban development can provide academic references for the integrated development of urban agglomerations. The results show that: (1) From 2000 to 2010, the average GDP growth rate of the cities in the YRD region showed a rapid growth trend but began to slow down after 2010, showing an outward spatial distribution pattern. (2) From 2000 to 2020, the growth rate of Shanghai’s investment in cities in the YRD showed a downward trend and an outward spatial diffusion. The growth rate of investment within the YRD showed a slowing trend from 2000 to 2015 and increased after 2015, showing a spatial distribution from northwest to southeast. From 2000 to 2020, the growth rate of investment from other cities in China to cities in the YRD showed a continuous upward trend, and spatially formed a distribution characteristic from northwest to southeast. (3) The growth of internal investment in the YRD and that of other cities across China can accelerate urban economic growth, and the growth of internal investment in the YRD has a greater role in promoting economic growth, indicating that the “agglomeration externalities” and “network externalities” at the urban agglomeration scale both can promote urban economic growth, but the effect of the “agglomeration externalities” within the urban agglomeration is more obvious. (4) The growth of investment in the core city Shanghai does not play a significant role in the long-term economic growth of cities in the region.

New economic geography (NEG) raises the question why the “agglomeration shadow” effect is significant in some urban regions but not others. This study attempts to answer this question in the context of China by examining the impact of industrial composition of core cities on regional urban systems. Based on the model of urban location from NEG, this study attempts to examine the population growth of six core cities and their urban systems in China. We find services exert a significantly negative effect on market potential, while that of manufacturing is positive. The results are robust in different spatial scales and time spans. This suggests that strong centralizing and agglomerative effects of higher order service sector are more likely to cast an agglomeration shadow on noncore cities in China’s regional urban systems. The differences in industrial composition can explain why an urban region centered on a large core city like Beijing is more likely to cast an agglomeration shadow on its surrounding cities compared to the Shanghai-centered urban region. The findings hold important implications for uneven development of regional urban systems and construction of metropolitan areas in China.

On the basis of MODIS Enhanced Vegetation Index time series data and multisource data, such as nighttime light data and China City Statistical Yearbook data, we investigated the differences in vegetation phenology along urban-rural gradients in urban areas of different sizes between coastal and inland cities in Liaoning Province, China. The results showed that the following: (1) the iterative extraction of urban built-up areas using the threshold method based on nighttime light data combined with the definition of urban built-up areas had high accuracy. (2) Additionally, we found that the start of the growing season (SOS) in Liaoning Province occurred between day 100 and day 180, while the end of the growing season (EOS) occurred between days 260 and 330. The difference in the SOS between coastal cities (i.e., Dalian, Yingkou, Panjin, Jinzhou, Huludao, and Dandong) and inland cities (i.e., Chaoyang, Fuxin, Tieling, Shenyang, Fushun, Liaoyang, Benxi, and Anshan) was 1.70 days. However, the difference in the EOS was more significant, i.e., the EOS in coastal cities occurred 4.47 days later than that in the inland cities. (3) In urban areas of different sizes, the ∆SOS and ∆EOS of inland cities had negative correlations with urban size. Specifically, when the urban size increased 10-fold, the ∆SOS and ∆EOS advanced by 10.03 and 5.71 days, respectively. In contrast, the ∆SOS and ∆EOS of coastal cities had positive and negative correlations with the urban size, respectively. Specifically, when urban size increased 10-fold, ∆SOS was delayed by 11.29 days while EOS was advanced by 8.83 days.

Two global cities of China, Beijing and Shanghai, have completely different development statuses with their hinterlands. There is a large economic development gap between Beijing and its hinterland, Hebei Province, while Shanghai has formed a highly integrated region with its hinterland, the Yangtze River Delta. According to the Outline of Collaborative Development of Beijing, Tianjin, and Hebei Province, enterprise linkages between Beijing and Hebei should be strengthened in order to narrow the economic gap between the center and the hinterland. On this basis, this paper proposes two hypotheses. (1) The economic gap between Beijing and Hebei has not really changed, because more enterprise linkages of Beijing are nonlocal. (2) The gradual narrowing of the economic gap between Shanghai and Jiangsu as well as Zhejiang is due to the fact that more enterprise linkages of Shanghai are local. We have used enterprise data on business registration from the State Administration for Industry and Commerce of China and have selected two indicators, namely, the number of headquarters-branches offices and the amount of enterprise investment, to examine the enterprise linkages between Beijing/Shanghai and their hinterlands as well as the hinterworld, and have verified these two hypotheses. The results show that nonlocal enterprise linkages based on the hinterworld are the main form in Beijing, while local enterprise linkages based on the hinterland are the main form in Shanghai. In addition, we have analyzed the mechanisms of formation of the enterprises linkages of the two cities and have put forward some policy suggestions.

Urban space is the spatial projection of various social and economic activities. Given the complexity of urban functions and the ongoing expansion of urban areas, the spatial differentiation of various economic activities within cities tends to become more and more clear; moreover, there tends to be spatial inequalities in resource allocation. Taking Beijing as an example, this study develops a spatial accessibility model at the town (jiedao) level by integrating the spatial distribution of economic activities with the transport system and evaluating the accessibility (at the spatial level) to various economic activities. The equality of the residents’ economic-related travel activity is also evaluated in line with the population distribution. The results show that the accessibility to economic activities generally decreases in going from the urban center to the peripheral suburbs, and this “core to edge” difference is readily apparent. In general, residents tend to choose areas to settle in which have a high degree of accessibility, however, the attractiveness of accessibility is constrained within certain limits, as evidenced by a reduction of population in the center of Beijing. Additionally, there are inequalities with respect to traveling experiences. For instance, 27.8% of residents experience very convenient travel conditions, mostly in the Xicheng, Dongcheng, and Haidian districts, and this equates to a high level of accessibility; about half of the residents in Beijing live in areas ranked as being of medium accessibility and where the distribution of economic activities and transportation facilities are insufficient. Residents living in the outlying Changping, Mentougou, Shunyi, and Fangshan districts have relatively poor access to transportation indicating a low level of accessibility. Overall, the evaluation method for spatial equality considers comprehensively the distribution of economic activities, transportation, and population distribution and can provide a reference framework for optimization of the urban spatial structure to improve urban spatial equality.

Little is known about the seasonal heterogeneity of land surface temperature (LST) and the interaction relationship between potential drivers in Sichuan Basin, China. In this study, based on exploring the spatial heterogeneity of LST in Sichuan Basin, China, multi-source remote sensing data as potential drivers were selected and a Geo-detector model was applied to analyze the main drivers and the interactive relationship between drivers on LST during different seasons. The results showed that the high-temperature areas in Sichuan Basin in different seasons all appeared in the cities near the high mountains on the edge of the basin. This phenomenon was summarized as “sinking heat island” by us. From the driving factors, the biophysical parameters (DEM, SLOPE and NDVI) had the greatest impact on LST in each season, reaching the peak in the transition season. The climate parameters (WIND, HUM, PRE and TEM) and socioeconomic parameters (LIGHT, POP and ROAD) also had a certain impact on LST. The influence of a single landscape parameter (SHDI, PD, LPI, ED and LSI) on LST is limited. From the effect of factor interaction on LST, the interaction of biophysical parameters, climatic parameters and landscape parameters from summer to the transitional season was strengthened obviously, and it showed a downward trend in the winter; in contrast, the socioeconomic parameters showed the opposite characteristics, indicating that the interaction between human activities and other factors affected LST more obviously in the winter. The results of this study are not only valuable for understanding the spatial features of LST but also important for formulating mitigation strategies and sustainable development of urban heat island in Sichuan Basin.

The reuse of existing industrial spatial resources in China’s major urban agglomerations is still very unbalanced and needs more in-depth research. This study used intensive evaluation technology for industrial land in Beijing, Tianjin, and Hebei to evaluate Tianjin and Hebei development zones, and took the Dingzhou Economic Development Zone as an example to evaluate and analyze the intensive use of enterprise land; it suggests the influencing factors for the intensive use of development zones and the measures that can take advantage of the potential of enterprise stock land so as to provide a basis for the rationale behind upgrading industrial land structures and the efficient use of industrial land in Beijing, Tianjin, and Hebei. The results show that the typical enterprise land use in the typical economic development zone is extensive, which suggests that the intensive use of land in the Dingzhou economic development zone is low and that there is still potential for land redevelopment. According to the classification system developed for available land, there is ample opportunity for land-use redevelopment in the development zone, especially in the area of approved but not supplied land and extended enterprise land. Therefore, the redevelopment of enterprise land could also provide a better land guarantee for industrial transfer projects in the equipment manufacturing industry. This study also offers strategies to redevelop available industrial land.

Loss of green space habitats and landscape fragmentation are important reasons for the decline in environmental quality, degradation of ecosystem functions, and decline in biodiversity. Quantifying the spatio-temporal characteristics of landscape fragmentation of green space and its relationship with urban expansion mode is an important basis for improving urban development mode and enhancing urban ecological functions. For this paper, we took the Beijing–Tianjin–Hebei (BTH) urban agglomeration as the research object, a typical rapidly urbanizing area. Through multi-scale landscape pattern analysis and statistical analysis, the spatial–temporal evolution characteristics of green space fragmentation in the BTH urban agglomeration from 2000 to 2020 and the influence of urban expansion were analyzed, and the land-use situation in 2030 was predicted by the Future Land Use Simulation (FLUS) model. The main conclusions are as follows: The BTH urban agglomeration has developed rapidly in the last 20 years, showing the characteristics of diffusion and corridor development. The intensity and pattern of urban expansion have significantly affected the pattern of green space, leading to the intensification of domestic green space fragmentation. Among them, urban expansion exerts most severe effects on the fragmentation of farmland, followed by grassland and water. The influence of urban expansion on the scale and fragmentation of forestland is limited. The forecast results in 2030 show that built-up areas may continue to occupy green space. The rate of occupation of farmland will slow down while that of grassland will intensify.

The continuous expansion of urban land has led to massive encroachment upon cropland. To examine the impacts of urban expansion on the loss and fragmentation of cropland in China’s nine major grain production areas (MGPAs), we used standard deviation ellipse, land use transfer matrix, land use dynamic degree, and landscape metric to explore the spatio-temporal evolutions, mutual transfer, and landscape patterns of cropland and urban land. The results show the following: (1) From 1995 to 2018, the areas of cropland in MGPAs showed a trend of “short-term increase—long-term decrease—short-term increase”, while that of urban land grew continuously; (2) Urban expansion is the main cause of cropland loss. The cropland area converted to urban land accounts for a large proportion (49.26%) of the total transfer of cropland to other land types, especially in the densely populated, rapidly urbanizing and industrializing Taihu Lake Plain, Jianghuai Region, and Pearl River Delta; (3) In most MGPAs, urban expansion has led to fragmentation of cropland, especially in the Pearl River Delta, as indicated by the significant change of patch density. However, in the Sanjiang Plain and Songnen Plain, a less pronounced or even reduced cropland fragmentation was observed due to the significant conversion of other land types to cropland under specific land policies. From these results, we suggest that the government should regulate the encroachment of urban land on cropland and the transfer of natural land to it, and encourage the rural land consolidation to increase the cropland.

This study analyzed data from 1995, 2005, and 2015 using mathematical calculations, spatial analysis, and a geographically weighted regression model. The results showed that from 1995 to 2015, the comprehensive regional development degree (RDD) of urban agglomeration in the middle of Jilin Province increased overall, with the average RDD increasing from 0.250 in 1995 to 0.323 in 2015. Especially in Changchun, a sub-provincial city, the RDD increased by nearly one-third, and the gap between this and other cities has been increasing. However, the ecosystem service value (ESV) decreased overall, with the average ESV decreasing from 108.3 in 1995 to 105.4 in 2015, and showed a strong spatial correlation. The maximum quantile in southeast–northwest direction was 1.712, with good homogeneity. The spatial influence coefficient of the RDD on the ESV showed a trend from positive to negative in the northwest–southeast direction. This value decreased continuously while the negative agglomeration area was gradually expanding, corresponding to the stressful effects of the RDD on ESV. The results of this study can provide a reference for urban planning and development as well as encourage reasonable regional spatial planning to ensure the sustainable development of urban agglomerations.

Rapid urbanization development and construction has seriously threatened the connectivity of habitat patches in cities and hindered the construction of ecological networks in highly urbanized areas. Among them, China is affected by early compressed urbanization, and the broken ecological space in cities and towns has attracted the extensive interest of researchers. To avoid the subjective randomness and single analysis of ecological space in urbanization areas, this paper takes the central urban area of Wuhan as the main research area. It comprehensively evaluates the ecological network space by combining the MSPA-MCR model. The main conclusions are as follows: (1) Identifying the ecological landscape types with important ecological significance in the study area: Core (88.29%), Islet (0.25%), Perf (0.63%), Edge (9.74%), Loop (0.22%), and Bridge (0.14%). Through the dPC landscape index, seven important ecological sources south of the middle reaches of the Yangtze River were identified. (2) According to the comprehensive factors of natural and human factors constructed by the MCR model, the minimum cumulative ecological resistance surface was established, with an average value of 2.65, a maximum value of 4.70, and a minimum value of 1.00, showing a trend that the ecological resistance values in the central and eastern parts are lower than those in the western part. (3) According to the standard deviation ellipse, the distribution direction of NE–SW in ecological sources was analyzed. The ecological sources distributed in the north were less, and the spatial distribution was scattered on the whole. The strong global positive correlation and local spatial aggregation characteristics of ecological resistance surface were evaluated according to spatial autocorrelation. Based on the gravity model, the interaction intensity of ecological corridors between source areas was evaluated, and the importance of ecological corridor protection and restoration was quantitatively analyzed. The research results provide scientific and reasonable references and a basis for ecological planning of Wuhan central city.

With the gradual expansion of benefits provided by islands to human wellbeing, it has become increasingly important to quantify the cultural ecosystem service functions of islands. In this study, the zone travel cost method (ZTCM) and individual travel cost method (ITCM) are used to assess the recreational and cultural ecosystem services value of the island region of Changhai County, China, and the recreational value of Xiaochangshan, Dachangshan, and Guanglu Islands based on questionnaire survey data. The results are as follows: (1) The overall recreational and cultural ecosystem services value of Changhai County in 2019 was 533.14 million USD, including a traveling cost of 395.71 million USD and consumer surplus of 137.43 million USD. (2) Further, based on the choice and consumption behaviors of tourists, multiple recreational values of the county were also inferred: the aesthetic experience presented the greatest contribution, while educational knowledge accounted for a lower percentage. (3) The recreational and cultural ecosystem services value 294.16, 60.03, and 143.26 million USD for Xiaochangshan, Dachangshan, and Guanglu Islands, respectively. Based on the findings of this study, future research will focus on the planning and development of Xiaochangshan Island tourism to maximize consumer surplus.

The construction of development zones is an important strategic measure for China to attract foreign investment and open up more extensively to the outside world; for this reason, such zones are also of great significance to China’s regional development. Although the economic effects of development zones have received extensive attention from scholars, the interaction between the development zone and the host city that surrounds it has, to date, remained unexamined. To fill this gap, this research constructed a panel measurement analysis framework and selected 46 of China’s national development zones established from 2004 to 2018 as study samples and used Granger causality test method to reveal the causal relationship between the total factor productivity of the development zones and their surrounding host cities. The consequences exhibited a long-term causality between the total factor productivity of the development zones and that of the host cities in all the panels. Short-term causality, however, was only identified in the eastern and western area panels. The development zone is shown to significantly promote the development of its host city, albeit with a certain lag effect; conversely, the support function provided by the host city to the development zone was found to remain weak. Our research results provide a new perspective on realizing a mutually beneficial interaction between development zones and their host cities.

A low-carbon economy is the most important requirement to realize high-quality integrated development of the Yangtze River Delta. Utilizing the following models: a super-efficiency slacks-based measure model, a spatio-temporal correlation model, a bivariate LISA model, a spatial econometric model, and a geographically weighted random forest model, this study measured urban industrial eco-efficiency (IEE) and then analyzed its influencing effects on carbon emission in the Yangtze River Delta from 2000 to 2017. The influencing factors included spatio-temporal correlation intensity, spatio-temporal association type, direct and indirect impacts, and local importance impacts. Findings showed that: (1) The temporal correlation intensity between IEE and scale efficiency (SE) and carbon emissions exhibited an inverted V-shaped variation trend, while the temporal correlation intensity between pure technical efficiency (PTE) and carbon emissions exhibited a W-shaped fluctuation trend. The negative spatial correlation between IEE and carbon emissions was mainly distributed in the developed cities of the delta, while the positive correlation was mainly distributed in central Anhui Province and Yancheng and Taizhou cities. The spatial correlation between PTE and carbon emissions exhibited a spatial pattern of being higher in the central part of the delta and lower in the northern and southern parts. The negative spatial correlation between SE and carbon emissions was mainly clustered in Zhejiang Province and scattered in Jiangsu and Anhui provinces, with the cities with positive correlations being concentrated around two locations: the junction of Anhui and Jiangsu provinces, and within central Jiangsu Province. (2) The direct and indirect effects of IEE on carbon emissions were significantly negative, indicating that IEE contributed to reducing carbon emissions. The direct impact of PTE on carbon emissions was also significantly negative, while its indirect effect was insignificant. Both the direct and indirect effects of SE on carbon emissions were significantly negative. (3) It was found that the positive effect of IEE was more likely to alleviate the increase in carbon emissions in northern Anhui City. Further, PTE was more conducive to reducing the increase in carbon emissions in northwestern Anhui City, southern Zhejiang City, and in other cities including Changzhou and Wuxi. Finally, it was found that SE played a relatively important role in reducing the increase in carbon emissions only in four cities: Changzhou, Suqian, Lu’an, and Wenzhou.

The global outbreak of the COVID-19 epidemic has caused a considerable impact on humans, which expresses the urgency and importance of studying its impacts. Previous studies either frequently use aggregated research methods of statistic data or stay during COVID-19. The afterward impacts of COVID-19 on human behaviors need to be explored further. This article carries out a non-aggregated study methodology in human geography based on big data from social media comments and takes Nanjing, China, as the research case to explore the afterward impact of the COVID-19 epidemic on the spatial behavior of urban tourists. Precisely, we propose the methodology covers two main aspects regarding travel contact trajectory and spatial trajectory. In contact trajectory, we explore three indicators—Connection Strength, Degree Centrality, and Betweenness Centrality—of the collected attractions. Then, in spatial trajectory, we input the results from contact trajectory into ArcGIS by using the Orientation–Destination Model and Standard Deviation Ellipse to explore the influences on the spatial pattern. By setting up comparative groups for the three periods of before, during, and after the COVID-19 in Nanjing, this study found that, in the post-epidemic era, (1) the spatial behavior of urban tourists showed a state of overall contraction; (2) the objects of contraction changed from urban architectural attractions to urban natural attractions; (3) the form of contraction presents concentric circles with the central city (Old City of Nanjing) as the core; (4) the direction of contraction heads to the large-scale natural landscape in the central city, which highlights the importance of green open spaces in the post-epidemic era.

This study analyzed the spatiotemporal distribution and driving factors of the floating school-age population in Liaoning Province, China from 2008 to 2020 using county-level statistical education data combined with spatial autocorrelation and the multiscale geographically weighted regression model. The major findings are as follows. From 2008 to 2020, the distribution of the school-age migrant population exhibited obvious spatial imbalance characteristics both in terms of the number and proportion of school-age migrants. Specifically, the school-age migrant population was concentrated in the municipal districts of large and medium-sized cities and continued to increase over time in the suburbs of large and medium-sized cities. Over the past 12 years, the distribution of the school-age migrant population in Liaoning Province exhibited significant spatial autocorrelation. From the number of school-age migrants, the cold and hot spot area expanded. Conversely, from the proportion of school-age migrants, the cold and hot spot area decreased gradually, whereas the cold spot area became more diffuse. Regarding the driving factors, the quantity and quality of teaching staff, the quality of teaching equipment and conditions, and the quality of the education environment played a role in promoting or restraining the differentiation of the school-age migrant population in Liaoning Province. Moreover, the degree of influence of the driving factors exhibited substantial spatial differences.

Three-dimensional laser scanning technology has been more mature, and its application fields are expanding. It is being used in key projects and important work such as ancient building recording, restoration and reconstruction. In this paper, the technology is applied to the 3D scanning, data splicing and model simplification of Heping temple building complex in Beijing. After innovative research on ancient architecture, it is found that the group layout, single form and local components of Heping temple building complex in Beijing show symmetry everywhere, vividly reflecting the extensive and profound ancient architectural culture and order. This points out a new direction for the development and application of 3D laser scanning technology and opens up a new path for the in-depth study of the protection of ancient buildings in China.

The transition of rural industrial land has a critical role to play in rural revitalization. The study of rural spatial governance is an important starting point for analyzing the processes and exploring the paths through which the transition of rural industrial land takes place. This study takes the case of Shunde District, China, a typical semi-urbanized area, as its research object and constructs an analytical framework for rural industrial land transition based on spatial governance; it uses this case to conduct an analysis of the spatiotemporal processes and dilemmas involved in rural industrial land transition. Hengding Industrial Park is taken as a specific example to study how the processes and mechanisms involved in the transition of rural industrial land work in practice from a spatial governance perspective, and the path of rural revitalization based on rural spatial governance is discussed. The conclusions are as follows: (1) the fragmentation of rural space, the difficulty of renewing rural industrial land, the chaos of ownership, and the incomplete mechanism of the differentiation and game of multiple subjects, are the main obstacles in the process of rural industrial land transition in Shunde District; (2) since the 1990s, the rural industrial land dominant morphology—including quantity, structure, and so on—and the recessive morphology, including property rights, organizational systems, and input–output efficiency, have all undergone significant changes; (3) the comprehensive governance of rural space under the analytical framework of “matter-ownership-organization,” is an important starting point for analyzing the process of transition of rural industrial land. The “top-down” and “bottom-up” approaches, combining rural spatial governance strategy and the effective participation of multiple subjects, are important means of promoting the transition of rural industrial land; (4) rural spatial governance is conducive to promoting the transition of rural land use and the healthy development of rural space. The experience of semi-urbanized regions with rural revitalization is of vital significance for other regions.

In recent years, the impact of land-use systems on global climate change has become increasingly significant, and land-use change has become a hot issue of concern to academics, both within China and abroad. Urbanization, as an important socioeconomic factor, plays a vital role in promoting land-use transition, which also shows a significant spatial dependence on urbanization. This paper constructs a theoretical framework for the interaction relationship between urbanization and land-use transition, taking the Yangtze River Delta as an example, and measures the level of urbanization from the perspective of population urbanization, economic urbanization and social urbanization, while also evaluating the level of land-use morphologies from the perspective of dominant and recessive morphologies of land-use. We construct a PVAR model and coupled coordination model based on the calculated indexes for empirical analysis. The results show that the relationship between urbanization and land-use transition is not a simple linear relationship, but tends to be complex with the process of urbanization, and reasonable urbanization and land-use morphologies will promote further benign coupling in the system. By analyzing the interaction relationship between urbanization and land-use transition, this study enriches the study of land-use change and provides new pathways for thinking about how to promote high-quality urbanization.